JP7110003B2 - Processing device, processing method, and program - Google Patents

Description

The embodiments of the present invention relate to processing apparatuses, processing methods, and programs.

A device is known that analyzes ground precipitation intensity from reflection intensity information observed by a weather radar. In some cases, conventional techniques cannot accurately analyze ground precipitation intensity.

JP-A-2003-344556

HYANGSUK PARK, A. V. RYZHKOV, D. S ZRNIC and KYUNG-EAK KIM, "The Hydrometeor Classification Algorithm for the Polarimetric WSR-88D: Description and Application to an MCS", WEATHER AND FORECASTING, American Meteorological Society, 2009, Volume24, p730- 748

A problem to be solved by the present invention is to provide a processing device, a processing method, and a program capable of deriving information on ground rainfall with higher accuracy.

A processing device according to an embodiment has an acquisition unit, a selection unit, and a derivation unit. The acquisition unit acquires observation information indicating the state of the atmosphere for each of a plurality of divided areas obtained by dividing a predetermined area in the azimuth direction, the distance direction, and the vertical direction, and quality information indicating the quality of the observation information for each of the divided areas. get. The selection unit selects a target divided area from among divided areas included in a group of divided areas having common positions in the azimuth direction and the distance direction based on the information acquired by the acquisition unit. The derivation unit derives the rainfall information of the divided area group based on the observation information of the target divided area selected by the selection unit.

The figure which shows the structure of the processing system 1. FIG. 2 is a conceptual diagram of radio waves emitted by the radar device 10. FIG. 2 is a diagram showing configurations of a processing device 20 and a display information generating device 50. FIG. 4 is a flow chart showing the flow of processing executed by the processing device 20; 4 is a diagram for explaining observation information D; FIG. 4 is a flowchart showing the flow of processing executed by a selection unit 26; FIG. 10 is a diagram showing an example of how ground meshes are selected; 4 is a flow chart showing the flow of processing executed by a derivation unit 28; FIG. 4 is a conceptual diagram of a method for calculating ground precipitation intensity set for each mesh block MB (ground mesh). 6 is a diagram showing an example of an image IM displayed on the display section of the terminal device 60. FIG.

Hereinafter, a processing apparatus, a processing method, and a program according to embodiments will be described with reference to the drawings.

(First embodiment)
FIG. 1 is a diagram showing the configuration of a processing system 1. As shown in FIG. A processing system 1 including a processing device 20 includes a radar device 10 , a processing device 20 and a display information generating device 50 . The radar device 10 and the processing device 20 communicate via a dedicated line or the like. The processing device 20 and the display information generating device 50 communicate via a network NW1 such as a LAN (Local Area Network). In addition, the display information generation device 50 communicates with the terminal device 60 via a network NW2 such as a WAN (Wide Area Network). Note that the processing device 20 and the display information generating device 50 may be formed integrally.

The radar device 10 includes an antenna 12 and an antenna-side control device 14 . The radar device 10 is, for example, a weather radar that observes atmospheric conditions. Also, the antenna 12 is, for example, a phased array antenna that includes a plurality of antenna elements and whose directivity angle can be changed electronically. Note that the radar device 10 may be a parabolic radar device. The radar device 10 rotates the antenna 12 in the horizontal direction while electronically scanning the elevation direction, thereby observing the state of the atmosphere in three dimensions. The antenna 12 transmits and receives radio waves under the control of the antenna-side control device 14 .

In the following description, the radar device 10 is described as being a dual polarized phased array radar device. radar device. A dual-polarization phased array radar system transmits and receives radio waves oscillating in the horizontal and vertical directions, and observes the state of the atmosphere based on the reception results.

The antenna-side control device 14 includes a radar-side control section 16 and an information storage section 18 . The radar-side control unit 16 causes the antenna 12 to transmit a fan beam with a wide elevation angle beam width. The radar-side control unit 16 performs DBF (Digital Beam Forming) processing. The radar-side control unit 16 receives the reflected radio waves returned from the transmitted fan beam hitting scattering objects such as precipitation particles at once, and simultaneously generates observation information (polarization parameters) for a plurality of elevation angle ranges.

The information accumulation unit 18 accumulates observation information acquired by the radar-side control unit 16 and transmits the accumulated information to the processing device 20 .

Here, the characteristics of the dual polarization phased array radar system will be described. FIG. 2 is a conceptual diagram of radio waves emitted by the radar device 10. As shown in FIG. For example, the radar device 10 radiates into the atmosphere a horizontally polarized wave as shown in the left diagram of FIG. 2 and a vertically polarized wave as shown in the right diagram of FIG. Then, the radar device 10 acquires the reflected radio waves that are returned after the two types of radio waves that have been radiated strike particles in the atmosphere. The radar device 10 acquires information on the shape of particles in the atmosphere in the vertical direction and the shape in the horizontal direction by acquiring the reflected radio waves of the two types of radio waves.

For example, raindrops in the atmosphere have different shapes depending on their size. Also, hail, hail, and snow have different shapes. For example, large raindrops may be flattened. The radar device 10 acquires information indicating the shape of the raindrops in the horizontal direction from the reflected radio waves with respect to the horizontal polarization, and obtains not only the strength (echo intensity) of the reflected radio waves but also the vertical direction of the raindrops from the reflected radio waves with the vertical polarization. Information indicating the shape can be obtained. The radar apparatus 10 can acquire information such as a reflection factor difference, an inter-polarization correlation coefficient, an inter-polarization phase difference change rate, and the like from the reflected radio wave. The reflectance factor difference is a parameter related to the aspect ratio of the particles. The polarization correlation coefficient is the correlation coefficient of the received power (received signal) of the horizontally polarized wave and the vertically polarized wave, which are the reflected radio waves. The inter-polarization phase difference change rate is a parameter related to the phase difference between the phase of the horizontally polarized wave and the phase of the vertically polarized wave, which are the reflected radio waves.

Also, when two kinds of radio waves pass through a particle having a flat shape or the like, a phase difference occurs between these radio waves. The radar device 10 can obtain inter-polarization phase differences, which are phase differences between the radar device 10 and the particles when they reciprocate with respect to each of the horizontal polarization and the vertical polarization. The inter-polarization phase difference change rate is the amount of change or differential amount of the inter-polarization phase difference in the distance direction.

FIG. 3 is a diagram showing the configuration of the processing device 20 and the display information generating device 50. As shown in FIG. The processing device 20 includes, for example, an acquisition unit 22 , a processing unit 24 , a selection unit 26 , a derivation unit 28 , an interpolation unit 30 , an information transmission unit 32 and a storage unit 40 . The acquisition unit 22, the processing unit 24, the selection unit 26, the derivation unit 28, the interpolation unit 30, and the information transmission unit 32 may be implemented by a processor such as a CPU (Central Processing Unit) executing a program. In addition, these functional units may be realized by hardware such as LSI (Large Scale Integration), ASIC (Application Specific Integrated Circuit), FPGA (Field-Programmable Gate Array), GPU (Graphics Processing Unit), It may be realized by cooperation of software and hardware. Further, the above program may be stored in a storage device in advance, or may be stored in a detachable storage medium such as a DVD or CD-ROM, and the storage medium is installed in the drive device of the processing device 20. may be installed on the storage device by The storage unit 40 is implemented by a storage device such as a RAM (Random Access Memory), ROM (Read Only Memory), HDD (Hard Disk Drive), flash memory, or the like.

The acquisition unit 22 acquires observation information from the radar device 10 . The acquired observation information is stored in the storage unit 40 . Note that the processing device 20 may be formed integrally with the radar device 10 . In this case, the acquisition unit 22 acquires observation information from the information storage unit 18 using a communication bus or the like in the device.

Based on the observation information acquired by the acquisition unit 22, the processing unit 24 performs processing for determining precipitation particles and acquires quality information. Information equivalent to the processing result of the processing unit 24 may be acquired from another device by the acquisition unit 22 . The details of the processing of the processing unit 24 and the function units (selection unit 26, derivation unit 28) described later will be described later.

Based on the information acquired by the acquisition unit 22, the selection unit 26 selects a target divided area from the divided areas included in the divided area group having the same horizontal position.

The derivation unit 28 derives rainfall information based on the observation information of the target divided area selected by the selection unit 26 . The interpolating section 30 interpolates the target divided area for the divided area group for which the target divided area has not been selected by the selecting section 26 in the divided area group. The information transmission unit 32 transmits the processing result of the processing device 20 to the display information generation device 50 .

The display information generation device 50 includes a display information generation section 52 and a display information transmission section 54 . The display information generation unit 52 generates display information (image information) for displaying information including the processing result on the display unit of the terminal device 60 based on the processing result transmitted from the information transmission unit 32 . The display information transmission section 54 transmits the display information generated by the display information generation section 52 to the terminal device 60 .

[Processing for Deriving Ground Precipitation Intensity]
FIG. 4 is a flow chart showing the flow of processing executed by the processing device 20. As shown in FIG. First, the acquisition unit 22 determines whether or not the observation information D for one period stored in the information storage unit 18 of the radar device 10 has been acquired (step S100).

The observation information D is information indicating the echo intensity acquired by the radar device 10 for each mesh (described later) and observation period. Note that the observation information D is not limited to information indicating the echo intensity, and may be any information that can determine the type of particles, the shape of particles, the presence or absence of particles, and the like.

FIG. 5 is a diagram for explaining the observation information D. FIG. Hereinafter, description will be made using XYZ coordinates as necessary. Observation information D is information obtained by driving the antenna 12 of the radar device 10 in the horizontal direction from the start point to the end point of the driving. The observation information D acquired between the start point and the end point is observation information acquired in one cycle. The mesh M is a divided area divided by a predetermined width in each of the distance direction (Y direction) from the radar device 10, the azimuth direction (X direction), and the altitude direction (Z direction). In the illustrated example, the mesh M is approximated by a cube because the observation information D is at a position sufficiently far from the radar device 10 . A set of meshes M having the same horizontal direction (distance direction and azimuth direction) and different only in the altitude direction (vertical direction) is referred to as a "mesh block MB". The mesh block MB is an example of "divided area group having a common horizontal position".

Returning to the description of FIG. When the observation information D for one period is obtained (or when the observation information D for a predetermined area is obtained), the processing unit 24 performs processing for determining precipitation particles (step S102). In this discrimination, it is discriminated whether precipitation particles (for example, hail, hail, ice crystals, dry snow, wet snow, rain) or non-precipitation echoes (ground clutter) exist in the mesh M, and the discrimination result is Classified by three-dimensional mesh.

The processing unit 24 performs a process of discriminating precipitation particles using a known method. The processing unit 24 applies a preset membership function to fuzzy theory to discriminate precipitation particles. A membership function is a function that outputs a degree of belonging of an element x of a set X to a set A to which fuzzy logic is applied. A set A is a set expressing that an element x of a certain set X belongs to the set A with ambiguity, and is characterized by a membership function.

For example, the membership function is a function that outputs a value closer to "1" when the degree of belonging to set A is higher, and outputs a value closer to "0" when the degree of belonging to set A is lower. For example, in determining precipitation particles, the processing unit 24 associates ground observation information, high-rise observation information, or temperature and humidity information obtained from model information with observation meshes to be observed. The ground observation information, high-rise observation information, or temperature and humidity information may be uniformly associated with observation meshes, or may be associated with different values for each observation mesh. Then, the processing unit 24 uses information associated with the observation mesh and fuzzy theory to determine precipitation particles included in the mesh. It should be noted that in this flowchart, regardless of the determination result, the process proceeds to the next step.

Next, the processing unit 24 acquires various quality information for each mesh M (step S104). The quality information is, for example, an index such as QIA (Quality Index Algorithm), SNR (Signal Noise Ratio), CSR (Clutter Signal Ratio). A detailed calculation method of QIA is shown in Park et al. (2009), which is Non-Patent Document 1, and can be used as an index for measuring the data quality of observed polarization parameters. QIA is an index that can estimate the quality of polarization parameter data from its own observation data, so it is effective to use QIA in a system that completes processing with information acquired from one radar device. . This data quality is affected by radar calibration error, radio wave attenuation, NBF (Nonuniform Beam Filling), partial beam blockage, variations in cross-polarization correlation coefficients in the scattering cross section, and reception noise. being considered. The target polarization parameters are reflection intensity Z, reflection factor difference ZDR, cross-polarization correlation coefficient ρhv, and cross-polarization phase difference change rate KDP. The input parameters (observation data) are horizontal reflection intensity, radar reflection factor difference, inter-polarization phase difference, inter-polarization correlation coefficient, and SNR (Signal Noise Ratio) may be directly input. , may be calculated from other input parameters. QIA calculated for the reflection intensity Z is QIAZ, QIA calculated for the reflection factor difference ZDR is QIAZDR, QIA is calculated for the inter-polarization correlation coefficient phv is QIAρhv, inter-polarization phase difference change rate KDP Let QIAKDP be the QIA calculated for . Smaller values of these represent poorer quality of the polarization parameters of interest.

“SNR” is an index obtained by subtracting the noise level from the received power received by the radar device 10 . A smaller "SNR" value indicates a poorer information quality (a higher level of noise included in the received power).

The "CSR" is obtained based on received power information before and after processing the influence of reflected radio waves corresponding to clutter (objects not to be measured). An influence is an influence on the processing result of the embodiment. A higher value of "CSR" indicates a poorer quality of information (more impact of clutter on the mesh M).

Next, the selector 26 selects a mesh (ground mesh) to be applied as ground rainfall information from among the mesh blocks MB (step S106). The selector 26 selects ground meshes to be used for deriving the ground rainfall intensity based on the precipitation particle determination results and quality information obtained in the processes of steps S102 and S104 and the received power. This processing will be described later (see FIG. 6).

Next, the deriving unit 28 selects a calculation method to be used for calculating ground precipitation intensity in the ground mesh selected in step S106 (step S108). Next, the derivation unit 28 derives the ground precipitation intensity in the ground mesh according to the ground precipitation intensity derivation method selected in step S108 (step S110). The processing of steps S108 and S110 will be described later (see FIGS. 6 and 8).

Next, the derivation unit 28 outputs the derived mesh analysis information (process result of step S110) (step S112). The derivation unit 28 outputs the mesh analysis information to the information transmission unit 32 or stores it in the storage unit 40, for example.

Next, the interpolator 30 determines whether or not ground precipitation intensity has been calculated for all ground meshes (step S114). If the ground precipitation intensity has not been calculated for all ground meshes (if there is a mesh block MB that does not have a mesh selected as the ground mesh), there are missing points. Perform interpolation processing. For example, the interpolation unit 30 performs three-dimensional interpolation processing for the missing points (step S116).

For example, if the ground precipitation intensity is calculated around the mesh block MB of the missing point and the missing point is isolated, the interpolation unit 30 can obtain a continuous distribution. Ground precipitation intensity can be interpolated for points. Interpolation is performed by three-dimensionally searching for meshes around the missing point mesh block MB (substantial XY two-dimensional search may also be used), and the ground mesh for which the ground precipitation intensity is calculated is found in the searched mesh. Interpolation is performed if there are more than a threshold. The interpolation method may be an extrapolation method, a nearest neighbor method, a linear interpolation method, a Cressmann interpolation method, or the like.

If the ground precipitation intensity has been calculated for all ground meshes, the processing of one routine of this flowchart ends. However, if there are missing points even after the processing in the interpolation unit 30 is performed, the processing may be terminated assuming that the ground precipitation intensity has been calculated for all ground meshes.

[Processing to select ground mesh]
FIG. 6 is a flow chart showing the flow of processing executed by the selection unit 26. As shown in FIG. This process is performed for each mesh block MB. First, the selection unit 26 acquires quality information about the mesh block MB to be inspected and information about the mesh M (step S200). The information about the mesh is the information about the position of the mesh M and the observation information D of the mesh. In this process, the lowest layer mesh of the mesh block MB is selected, and the process is started sequentially from this mesh. Hereinafter, the mesh M to be processed will be referred to as a "target mesh".

Next, the selection unit 26 determines whether or not the target mesh is at or below the allowable altitude (step S202). Check whether the altitude of the target mesh is located below the altitude allowed as "ground precipitation". If this is not satisfied (if the target mesh is not below the allowable altitude), it is determined that there is no mesh M corresponding to the ground mesh (missing measurement). Then, the mesh block MB to be processed next is selected, and the processing of this flowchart is performed. In the processing after step S204, each input information value (such as the information obtained in steps S102 and S104 in FIG. 3) is used.

If the target mesh is below the allowable altitude, the selection unit 26 determines whether the radar reception intensity Pr of the reflected radio wave received by the radar device 10 is above the threshold (step S204).

When the radar reception intensity Pr is equal to or greater than the threshold, the selection unit 26 determines whether or not the particles are determined to be precipitation particles as a result of particle determination (step S206).

When the particles are determined to be precipitation particles as a result of the particle determination, the selection unit 26 determines whether or not the "SNR" is equal to or greater than the threshold (step S208).

If the "SNR" is greater than or equal to the threshold, the selector 26 determines whether or not the "CSR" is less than or equal to the threshold (step S210).

When "CSR" is equal to or less than the threshold, the selection unit 26 determines whether "QIA" is equal to or greater than the threshold (step S212).

When "QIA" is equal to or greater than the threshold, the selection unit 26 selects the target mesh as the ground mesh (step S214). “QIA” in step S212 is “QIAZ” calculated for the reflection intensity Z, “QIAZDR” calculated for the reflection factor difference ZDR, and “QIAρhv” calculated for the cross-polarization correlation coefficient ρhv. , one or more "QIA" among "QIAKDP" calculated for the inter-polarization phase difference change rate KDP. When multiple "QIAs" are used for processing, a threshold is set for each "QIA", and the threshold is compared with the QIA corresponding to the threshold.

In the processing of steps S204 to S212, if a negative determination is made, the selection unit 26 selects the next target mesh and repeats the above processing. This completes the processing of one routine in this flow chart.

Although the order of the processes described above may be changed as appropriate, the process of step S202 is performed with priority over the processes of steps S204 to S212, thereby reducing the processing load and increasing the efficiency of the process. improve. This is because information in which the radar reception strength Pr is not equal to or greater than the threshold is information that is not suitable to be used as information in the first place.

In the example shown in FIG. 6, the inspection is passed (selected as the ground mesh) when "AND" is established for all the conditions, but the conditions for passing the inspection are not limited to this. If the inspection fails during the inspection, the mesh M immediately above the mesh to be inspected (target mesh) is inspected. By repeating this, a ground mesh or missing measurement is defined for one mesh block MB in the vertical direction. Furthermore, by expanding this in the horizontal direction, a ground mesh is defined on a two-dimensional plane within the observation area of the radar device 10 .

FIG. 7 is a diagram showing an example of how ground meshes are selected. For example, it is assumed that the process is executed from the mesh block MB1 in the minus X direction in FIG. For example, in mesh block MB1, a mesh given with "o" is selected as a ground mesh, in mesh block MB2, it is determined that there is no ground mesh block, . . . "o" is selected in mesh block MB10. The given mesh is selected as the ground mesh.

[Processing for determining calculation method]
FIG. 8 is a flow chart showing the flow of processing executed by the derivation unit 28. As shown in FIG. A specific example of the method for calculating the ground precipitation intensity determined in the processing of this flowchart will be described later.

First, the derivation unit 28 determines whether or not the ground mesh is at or below the lower end height of the molten layer (step S300). Here, the altitude (upper end, lower end) of the melted layer derived from information on temperature and humidity obtained from ground observation information, upper observation information, or model information is used. The height of the molten layer may be derived by processing device 20 or may be obtained from another device. Moreover, the processing device 20 may derive the altitude of the molten layer based on the observation information acquired from the radar device 10 .

When it is determined that the ground mesh is equal to or lower than the lower end height of the melted layer, the derivation unit 28 determines whether the determination result of precipitation particles is rain (step S302). When the precipitation particle determination result is rain, the derivation unit 28 determines whether or not the reflection intensity Z and the inter-polarization phase difference change rate KDP are equal to or greater than their prescribed thresholds (step S304). Note that the derivation unit 28 determines whether the comparison target (reflection intensity Z and inter-polarization phase difference change rate KDP) is included in a predetermined range defined for each, instead of determining whether or not it is equal to or greater than the threshold value. can be determined.

If the reflection intensity Z or the inter-polarization phase difference change rate KDP is equal to or greater than the threshold, the derivation unit 28 determines to adopt the derivation method for rainfall area 1 (step S306). Rainfall area 1 is an area where a relatively large amount of precipitation is predicted.

If the reflection intensity Z or the inter-polarization phase difference change rate KDP is not equal to or greater than the threshold, the derivation unit 28 determines to adopt the derivation method for rainfall area 2 (step S308). The rainfall area 2 is an area predicted to have a relatively small amount of rainfall.

In this way, when it is determined that the determination result of the precipitation particles derived based on the real-time observation information acquired from the radar device 10 in steps S302 to S308 is rain, the derivation unit 28 uses the rainfall area calculation method to select. Further, the rainfall area is divided into a rainfall area 1 and a rainfall area 2 according to the reflection intensity Z and the threshold value of the inter-polarization phase difference change rate KDP.

When it is determined in step S300 that the altitude is lower than the bottom altitude of the melting layer (when it is determined that it is less than the bottom altitude of the melting layer), ground precipitation is expected to be rain, but step S302 In the processing of step S312, if the determination result of the precipitation particles is not rain (that is, solid-phase particles are determined), the derivation unit 28 determines to adopt the method of deriving the snowfall area. move on.

When it is determined in the process of step S300 that the ground mesh is not below the lower end height of the molten layer, the derivation unit 28 determines whether or not the above ground mesh is below the upper end height of the molten layer (step S310). If the ground mesh is equal to or lower than the upper end height of the molten layer, the derivation unit 28 determines to adopt the method of deriving the molten layer area (step S314).

If the ground mesh is not equal to or lower than the top altitude of the melting layer, the derivation unit 28 determines to adopt the method of deriving the snowfall area (step S312). As a result, the processing of one routine in this flowchart ends.

[Specific example of precipitation intensity calculation method]
(rainfall area 1)
In the rainfall area 1, the ground rainfall intensity Rr is calculated, for example, by the following formula (1).
'Z' is the reflection intensity, 'B' is the first parameter, and 'β' is the second parameter.
Z=B× ^Rrβ (1)

(Rainfall area 2)
In the rain area 2, the ground precipitation intensity R is calculated, for example, by the following formula (2).
“α” is the third parameter, “b” is the fourth parameter, and “f” is the radio wave transmission frequency of the radar device 10 . “KDP” is the inter-polarization phase difference change rate.
R=α×(KDP/f) ^b (2)

(snowfall area)
In a snowfall area, the ground precipitation intensity Rs is calculated by, for example, the following formula (3). "Bs" is the fifth parameter and "βs" is the sixth parameter.
Z=B _s ×Rs ^βs (3)

(melting zone)
In the melted layer area, the ground precipitation intensity is calculated using the ground mesh values immediately below the upper edge of the melted layer and directly above the lower edge of the melted layer (immediately before the lower edge and immediately after the upper edge when viewed in a two-dimensional plane). Desired. The method of obtaining may be, for example, Equation (4) using a weighted average method as shown below, or a method using a linear interpolation method or the like. Here, "m" is the distance from the upper end of the melted layer in the ground mesh to be calculated, and "n" is the distance from the lower end of the melted layer in the ground mesh to be calculated.
Rm=(m/m+n) ^* Rr+(n/m+n) ^* Rs (4)

As described above, the processing device 20 calculates the ground precipitation intensity for the selected ground mesh using the ground precipitation intensity calculation method suitable for the ground mesh. FIG. 9 is a conceptual diagram of a method for calculating ground precipitation intensity set for each mesh block MB (ground mesh). As shown in FIG. 9, the method for calculating ground precipitation intensity is set for each mesh block MB. Information to be provided to the terminal device 60 is generated based on the ground precipitation intensity calculated for each mesh block MB.

The display information generation unit 52 of the display information generation device 50 generates information suitable for the end user with respect to the two-dimensional distribution of ground precipitation intensity within the observation range of the radar device 10 . "Information suitable for end-users" includes, for example, spatial cumulative rainfall within an area, hourly rainfall accumulated over a specified period of time, inflowing rainfall in a certain point or area (how much is flowing into rivers and manholes), soil It is the effective rainfall that indicates the impact on the In addition, the processing device 20 may limit the amount of information flowing to the subsequent stage at this point in order to reduce the amount of information.

Also, the display information generator 52 generates rainfall information to be provided to the user, using the ground precipitation intensity derived for each mesh block MB. In addition, the display information generation unit 52, for example, determines whether the ground precipitation intensity in a local area is equal to or greater than a set threshold, and if it is determined to be equal to or greater than the threshold, the threshold is exceeded. Generates information indicating an alert indicating Information indicating this alert is an example of rainfall information. Also, the information itself indicating the local ground precipitation intensity may be used as the image information.

In addition, the display information generation unit 52 generates the output results of the numerical weather prediction model, surface weather observation information, remote sensing meteorological instrument information, land use information, terrain information, river basin information, geological information, route information, traffic information, and the like. This information may be combined with local area ground precipitation intensity to generate rainfall information. For example, the display information generation unit 52 generates information indicating that transportation facilities will be affected, information indicating the possibility of danger occurring in areas with weak ground, information indicating that rivers will rise, and the like.

FIG. 10 is a diagram showing an example of the image IM displayed on the display section of the terminal device 60. As shown in FIG. For example, as shown in FIG. 10, the image IM includes information indicating the intensity of rain and information indicating a warning that the river may rise. By referring to the image IM, the user can recognize the rain distribution and the danger caused by the rain.

[summary]
According to the processing device 20 of the present embodiment, by using the information obtained from the dual-polarization phased array weather radar and observed without gaps at a high frequency, spatio-temporally continuous observation information can be obtained at intervals of approximately 30 seconds. From this, it becomes possible to analyze the distribution and time variation of ground precipitation intensity with high frequency and accuracy, and to provide users with frequent rainfall information. Furthermore, by combining local ground precipitation intensity as observation information with land information, route information, and traffic information to generate rainfall information, human and economic risks due to heavy snow can be determined with high accuracy and speed. It becomes possible to notify and provide information to the user in an accurate form. Specifically, by providing information through application software for the general public, SNS, etc., it is expected to help alert the general public and encourage evacuation. In addition, it is expected that the system will effectively contribute to speeding up responses to sudden heavy rains by local governments, road administrators, railway operation administrators, bus operation administrators, and the like.

[Comparison]
Here, when obtaining a two-dimensional distribution of ground precipitation intensity from information observed by weather radar, the information observed by multiple radar devices is used and combined to obtain the optimum ground precipitation intensity distribution. There may be However, for geographical reasons (geographical environment in which multiple radar devices cannot be installed) and economic reasons (difficult to deploy multiple radar devices in a network), the ground precipitation intensity is measured as a single unit. Accurate analysis by a single radar device is necessary, but it is difficult to say that a system for realizing this has been established yet.

For example, when obtaining the ground precipitation intensity distribution with a single parabolic weather radar device, each region is based on sparsely observed information for each elevation angle, altitude information, and a map prepared in advance. The elevation angle information applied as "ground precipitation intensity" was defined and used as the ground precipitation intensity distribution.

However, in this method for the parabolic radar system, since spatially sparse information is input, information distant in the altitude direction from the ground is also treated as the ground precipitation intensity, and there is a problem in accuracy.

Also, when altitude information and maps are handled statically, there are cases where mesh information closest to the ground and with good quality is not applied. High temporal resolution information is necessary to capture sudden weather phenomena. The above method requires 3D information, and parabolic weather radars generally take 5 to 10 minutes to acquire 3D information, so it is difficult to provide ground precipitation intensity in real time. There is

Heavy rains that cause disasters and cause economic losses often occur locally in a short period of time. It is important to be able to analyze frequently. However, for the reasons described above, there is a problem that it is difficult to provide ground precipitation intensity information with high accuracy and high time resolution, particularly using single weather radar information.

In addition, with the information obtained by the single-polarization weather radar, it is sometimes impossible to observe the rainfall intensity distribution behind the heavy rainfall area due to rainfall attenuation. Furthermore, since the quality information (including particle discrimination etc.) that can be acquired is limited, it is difficult to optimize the application information using this quality information.

On the other hand, in this embodiment, observation information including polarization parameters can be obtained using a dual-polarization weather radar, which can be used to effectively correct rainfall attenuation and calculate quality information. be. Then, by effectively using the polarization parameter observation information obtained by the dual-polarization phased array weather radar, which is observed without gaps at high frequency, and the quality information obtained from the obtained polarization parameter observation information, a single It is possible to provide spatio-temporally continuous and highly accurate rainfall information based on ground precipitation intensity distribution. This can be expected to improve the accuracy of judgments on disaster risks and risks that hinder economic activities.

According to the embodiment described above, observation information indicating the state of the atmosphere for each of a plurality of divided areas obtained by dividing a predetermined area in the horizontal direction and the vertical direction, and quality information indicating the quality of the observation information for each of the divided areas. a selection unit that selects a target divided area from divided areas included in the group of divided areas having the same horizontal position based on the information obtained by the obtaining unit; By having the derivation unit that derives the rainfall information based on the observation information of the target divided area selected by the unit, the information on the ground rainfall can be derived with higher accuracy.

While several embodiments of the invention have been described, these embodiments have been presented by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and modifications can be made without departing from the scope of the invention. These embodiments and their modifications are included in the scope and spirit of the invention, as well as the scope of the invention described in the claims and equivalents thereof.

1 processing system 10 radar device 20 processing device 22 acquisition unit 24 processing unit 26 selection unit 28 derivation unit 30 interpolation unit 32 information transmission unit 40 storage unit , 50... display information generation device, 52... display information generation unit, 54... display information transmission unit, 60... terminal device

Claims (11)

Acquiring observation information indicating the state of the atmosphere for each of a plurality of divided areas obtained by dividing a predetermined area in the azimuth direction, the distance direction, and the vertical direction, and quality information indicating the quality of the observation information for each of the divided areas. an acquisition unit;
a selection unit that selects a target divided area from among divided areas included in a group of divided areas having common positions in the azimuth direction and the distance direction based on the information acquired by the acquisition unit;
a derivation unit that derives rainfall information of the divided area group based on the observation information of the target divided area selected by the selection unit;
A processing device comprising: The selection unit selects the target divided area based on a comparison between a numerical value indicated by the quality information and a threshold.
2. The processing apparatus of claim 1. The quality information includes an index indicating the quality of the reflection intensity, an index indicating the quality of the reflection factor difference, an index indicating the quality of the inter-polarization correlation coefficient, and an index indicating the quality of the inter-polarization phase difference change rate. , containing one or more indicators,
3. The processing apparatus according to claim 1 or 2. The quality information further includes an index based on the received power received by the radar device that acquired the observation information and noise included in the received power, and before and after processing for excluding signals indicating clutter from the observation information. an index derived based on the received power of and/or
4. A processing apparatus according to claim 3. The acquisition unit further acquires a result of particle discrimination for each of the divided regions derived based on the observation information,
The selection unit further selects the target divided area based on the result of the particle discrimination.
5. A processing apparatus as claimed in any one of claims 1 to 4. The acquisition unit further acquires the radar reception strength of the radar device that acquired the observation information,
The selection unit selects the target divided area based on the radar reception intensity acquired by the acquisition unit.
6. A processing apparatus according to any one of claims 1-5. The derivation unit derives the rainfall information of the divided area group based on a comparison between the distribution of the melting layer and the position in the altitude direction of the target divided area selected by the selection unit.
7. A processing apparatus according to any one of claims 1-6. The observation information is information obtained by a radar device that transmits and receives dual polarized waves,
4. A processing apparatus according to claim 3. The selection unit selects the target divided area from each of the plurality of divided area groups included in the observation area of the observation target,
The derivation unit derives the rainfall information of the divided area group based on the observation information of the selected target divided area.
9. A processing apparatus according to any one of claims 1-8. the computer
Observation information indicating the state of the atmosphere for each of a plurality of divided areas obtained by dividing a predetermined area in the azimuth direction, the distance direction, and the vertical direction, and quality information indicating the quality of the observation information for each of the divided areas. ,
selecting a target divided area from among divided areas included in a group of divided areas having common positions in the azimuth direction and the distance direction based on the acquired information;
Deriving rainfall information of the divided area group based on the observation information of the selected target divided area;
Processing method. to the computer,
Acquisition of observation information indicating the state of the atmosphere for each of a plurality of divided areas obtained by dividing a predetermined area in the azimuth direction, the distance direction, and the vertical direction, and quality information indicating the quality of the observation information for each of the divided areas. ,
selecting a target divided area from divided areas included in a group of divided areas having common positions in the azimuth direction and the distance direction based on the acquired information;
Deriving the rainfall information of the divided area group based on the observation information of the selected target divided area;
program.

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